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Humidity of Crawley, 38 Bolton Road RH10 7LS Crawley, has been collected from the google search and the website timeanddate.com. The average humidity of the city has been taken from January 14 to January 23 from the website. The humidity values are arranged in a table and then mean, median, mode, standard deviation, etc are calculated. The graphs and tables are also analyzed from the data which are put in the excel file. Task 4 is related to the forecasting of the humidity by analyzing the straight line equation from the graphs inputting the m and c value in the y= mx+ c.

Task 1 is related to the formation of a table by arranging the data set date-wise, taking the average humidity values of the Crawley city.

The second task is related to the graphs and figure depiction from those data using ms excel. Two types of graphs are used to understand the input values and humidity track of those days in Crawley city. Column chart and line chart have been used to predict the graphical representation of humidity from 14th to 23rd January in Crewley.

**Column chart**

The highest humidity recorded on 18th January (96%) and lowest on 20th January (62%).

To calculate the mean, median, mode, and standard deviation, the first task is to arrange the data set according to the lowest to highest value. Then, median and mode can be calculated easily.

The data set has been arranged in increasing order to evaluate the mean, median, and mode of the data set. After calculating variances, the calculation of standard deviation would become easy. All requirements are discussed in this chapter with a detailed description.

The increasing order of the 10 days data set of average humidity from 14th January to 23rd January in the city of Crawley is= 62, 72, 76, 76, 79, 81, 85, 88, 93, 96.

**Mean**

Mean is the average of the data set. It can be calculated by adding the values of the number of data sets and then dividing it by the number of data sets taken (Arumugam and Rajathi, 2020).

Therefore the summation of the data set would be 14th+ 15th+ …23rd= 720. Therefore, the mean value of the data set would be 720/10 which is equal to 72.

Mean humidity of the city is 72%.

**Median**

Median is the moderate value of the data set which can be evaluated by arranging the data set in increasing order (Ranjeeth *et al.* 2020). Then the middle value would be the median of the data set.

The median value of the data set is equal to (79+81)/2= 80.

Mean value of the humidity data set is 80.

**Mode**

Mode value can be calculated by using the techniques which are discussed in this section. The increasing order must be followed properly then it can be evaluated by finding the repeating number that means which occurs for maximum times (Hadi and Tola, 2019).

76 are repeated two times and therefore the mode value of the data set would become equal to 76.

**Range**

The range of any data set means the difference between the largest value and lowest value of the data set (Bose and Emirates, 2018). The maximum value is 96 and minimum value is 62. Therefore the range of this data set is equal to (96-62)= 34.

The range of the data set is 34.

**Standard deviation**

To calculate the standard deviation, the first task is to calculate the sample variances. The square root value of the variance is equal to the standard deviation (Kaliyadan and Kulkarni, 2019)

The value of standard deviation would be √ [ **Σ **(x- x?)^2 / n-1].

**Σ **(x- x?)^2 = 1074. Here, n =10 is the number of records that are actually taken.

Therefore the value of standard deviation (√ [ **Σ **(x- x?)^2 / n-1]) = **13.76**

- The linear equation for the straight line is described in the below figure including gradient (m) and interpretation (c) evaluation.

The equation would be y = mx+ c.

But in this case the gradient would be negative as with time the humidity value decreases from day 1 (14th Jan) to the day 10 (23rd Jan). To evaluate the gradient and y-axis interpretation the best fit line should be drawn and it would help to evaluate the gradient and constant values of the equation.

The coordinates of the equation would be (1, 9.3), (2, 8.5), (3, 8.8), (4, 7.2), (5, 9.6), (6, 8.1), (7, 6.2), (8, 7.6), (9, 7.9), (10, 7.6).

The value of m can be calculated as given below. The equation y= -mx + c would be followed in this case. Therefore, the value of m can be calculated as m = - (y-c)/x. The range of the data set is 34 for the 10 values. Therefore the gradient would be equal to - 3.4 and c also can be calculated by using the pictorial graphs.

- Similarly, c value can be calculated as c = - (y-mx). By following the equation c value can be calculated and it would help to determine the best fit equation. For x= 0, y would be equal to the c. The value of c would be equal to the 7.2 as median of the equation would become 72.
- From the graphical representation, c value and m value can be calculated.

The value of c = 7.2 and the value of m = -3.4. Calculated humidity for the 11th and 13th day can be calculated by extending the linear equation for x= 11 and 13.

Humidity on the 11th day would become 30.2% and the 13th day would become 37% as per the mathematical calculation.

Mean value= 72

Mode= 76

Median= 80

Range= 34

Standard deviation= 13.76

The value of m and c are -3.4 and 7.2.

Humidity on the 11th day= 30.2%

Humidity on the 13th day= 37%.

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